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Comment by PartiallyTyped | Hacker News Reader

I think I have a decent CV, with quite a bit of experience for a master's student. I have been searching for a job in MLE, for a bit now with very little to show for it, as I am either getting no responses, or responses claiming that they are looking for more experienced people, and particularly those that had experience with a particular stack.

In all honesty, after 6 years of studying, with 4 of those years studying ML, to be told that I lack experience with some particular stack as the ~~excuse~~ reason for rejection feels like a slap in the face.

And all that ignoring everything that expects 3+ years experience for entry level positions.

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I suspect they are looking for experienced ppl because they don't have one and don't exactly know how to manage ML and what to do with it and hope someone else will come and show them.

Start building projects on your own with the most common tooling. Having something to show cuts down barriers.

Reading comments like this is a bummer. I am currently doing my masters with a focus on NLP. At this point I'll be pretty happy to get a job even if it just boils down to only deploying ML models. Even for such a role of companies expect years of experience or a PhD I don't know how I can even get a job in the first place

I sometimes interview candidates for ML engineering roles, and let me tell you most of them have trouble with basic concepts. It's great when I find someone fluent, for a change.

Basic concepts referring to what precisely?

All these fields have that problem. There are people who are great at aping the signals (and even beating publication metrics) but really don't know anything. When they show up on a job, they get put into a PM (or actual management) role to limit the damage they can do. They learn enough lingo to be able to convince 90% of people they know what they're talking about (congrats on being in that other 10%, though) and will move up forever. Meanwhile, people who actually know their shit are usually too busy actually being smart to play the games necessary to get themselves hired in a hyper-competitive job market. So it goes.

I can only speak for Boston area, but I've been on teams who regularly welcome those with only 1-2 years of experience (even if it wasn't that relevant, as long as they had relevant schooling). I don't know if you consider that positive or negative evidence, but there it is.

I have been in a similar position with NLP - either you already have a lot of experience (maybe even a PhD) or you're a mathematician or statistician. Otherwise you're left out.

Funny enough, my experience is NLP and DeepRL.

Your best chance might be to apply at small companies. They often have data and want to take advantage of it but haven't so far. Of course they're not doing any research or are Google, Amazon, etc. but hey.

You have to be doing something wrong or applying for the wrong types of jobs (lots of MLE jobs are just glorified dba jobs at certain job companies).

That is why I am doing a Post Doc

May I ask what you're working on?

On causality

There is this interpretation of Bayesian networks that the parents are the true causes of a node and to predict what happens if you change a variable you need to remove the edges from the parents to that variable from the network. And then I study what you can do with that method

where are you located?

Europe. I am open to relocating pretty much anywhere in Western Europe or Scandinavia so my horizons are pretty open.

So central or eastern Europe ... yeah, thats gonna be tough!

No, actually in Scandinavia.

As a fellow Scandinavian I was in a similar position as you 2018, except that I was looking for MLE job with a (Software) Robotics background.(because beside ABB there were no robotics interest there).

Tl;dr I moved to Japan and worked in ML (ish) job. Once you start working it becomes remarkably easier to not be scoffed for lack of experience (even if you learned very little in that job)

Job security is high in Scandinavian countries and as an consequence people hire very risk-averse. risky/not so established jobs such as ML positions, they'll be actively looking for reasons NOT to hire you

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